A model of muscle-tendon function in human walking at self-selected speed

Although joint biomechanics and whole-body energetics are well documented for human walking, the underlying mechanisms that govern individual muscle-tendon behaviors are not fully understood. Here, we present a computational model of human walking that unifies muscle and joint biomechanics with whole-body metabolism for level-ground walking at self-selected speed. In the model, muscle-tendon units that dorsiflex the ankle, and flex and extend the knee, are assumed to act as linear springs upon neural activation; each muscle-tendon is modeled as a tendon spring in series with an isometric force source. To provide the mechanical power lost in step-to-step gait transitions, a Hill-type soleus muscle is modeled to actively plantar flex the ankle using muscle state and force as reflex feedback signals. Finally, to stabilize the trunk during stance, and to protract and retract each leg throughout the swing phase, two mono-articular Hill-type muscles actuate the model's hip joint. Following a forward dynamics optimization procedure, the walking model is shown to predict muscle and joint biomechanics, as well as whole-body metabolism, supporting the idea that the preponderance of leg muscles operate isometrically, affording the relatively high metabolic walking economy of humans.